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Course Outline

Introduction to Kubiya AI

  • A comprehensive overview of Kubiya AI and its core capabilities.
  • Understanding the role of AI-powered automation in cloud environments.
  • Identifying key features of Kubiya AI relevant to cloud management.

Cloud Resource Automation

  • Leveraging Kubiya AI to automate resource provisioning workflows.
  • Orchestrating cloud environments via AI-driven processes.
  • Integrating with leading cloud services including AWS, Azure, and Google Cloud.

Optimizing Cloud Costs with AI

  • Applying AI-based techniques for cost optimization.
  • Monitoring cloud usage and expenses in real-time.
  • Utilizing AI-generated recommendations to reduce cloud spend.

Security Enhancements Using Kubiya AI

  • Employing AI-driven monitoring for threat detection and security oversight.
  • Automating responses to security incidents.
  • Implementing AI-assisted compliance checks.

Hands-On with Kubiya AI

  • Configuring and setting up Kubiya AI for operational cloud tasks.
  • Practical labs focused on automating cloud resource management.
  • Practical labs dedicated to implementing cost optimization strategies.

Challenges and Future Trends

  • Addressing scalability and performance challenges in cloud AI automation.
  • Exploring emerging trends in AI applications for cloud operations.
  • Looking ahead at the future of AI-powered cloud management.

Advanced Kubiya AI Concepts

  • Investigating advanced AI features for sophisticated cloud automation.
  • Implementing advanced techniques for security and cost savings.
  • Customizing Kubiya AI configurations for specific cloud environments.

Summary and Next Steps

Requirements

  • Practical experience with major cloud platforms such as AWS, Azure, or Google Cloud.
  • A foundational understanding of DevOps practices.
  • Familiarity with common automation tools.

Target Audience

  • Cloud engineers.
  • Operations managers.
 14 Hours

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